Data platform and Bayesian forecasting of Swiss lakes – DATALAKES
Co-PIs:
- Jonas Šukys (Eawag)
- Damien Bouffard (Eawag)
- Johny Wuest (EPFL)
- Siddhartha Mishra (ETH Zürich)
Project presentation
April 20th 2018
Problem:
- Increasing pressure on lakes needs scientific support
- 3D numerical simulations of lakes require input data – uncertainty quantification in parameters & forecast
- New L’EXPLORE platform in Lake Geneva – increasing availability of high resolution data
Solution:
- Sensor-to-frontend open data platform
- Physics-driven hydrodynamic models
- Data-driven modeling of input data processes
- Parallel Bayesian inference – MCMC with ABC or PF
- Multi-level speedup – hierarchical numerical models
- Powered by Renku, the SDSC-developed platform for transparency and reproducibility in science
Impact:
- Real time monitoring & future forecast of lakes
- Platform for large-scale interdisciplinary collaborations
- Research in hydrological / ecological lake modeling
- Scientifically grounded water resources management
